FloodSENS
Description
FloodSENS is a explanatory machine learning algorithm that uses satellite imagery and topographic data to accurately identify, map and monitor flooded area globally, across diverse conditions. It provides timely flood information for insurance, humanitarian aid, and disaster management.
Disaster Risk Response Stage
Preparedness
Response
Response
Category
None
Temporal Use
Current observation
Retrospective analysis
Input Network
EOTEC DevNet
Input Network Member
EOTEC DevNet
Provider Organization
RSS-Hydro
Point of Contact
Guy Schumann
E-mail
Geographic Domain
Regional
Geographic Product Locations
Global
Geographic Product Locations - Detailed
Producing Daily Global Coverage?
No
Globally Extensible
No
Product Delivery Latency
Under 30 minutes from image availability.
Data Type
Raster
Associated Capacity Development Resources
None
Product Format
GeoTIFF
Archived
No
Tailored Service Available
Yes
License Type
P
Spatial Extent
Same as extent of the satellite image used - can be multiple within one regional AOI.
Spatial Scale
Spatial scale of the flooded area at a pixel spacing of 10 m (highest).
Caveats
Limited under dense cloud cover, dense vegetation and dense urban areas.
Frequency
Once or twice per week, depending on Sentinel mission.
Overpass Latency
Once or twice per week, depending on Sentinel mission.
Downlink Latency
A couple of hours for image availability.
Processing Latency
Less than 30 minutes
Impacted By Cloud Shadows
Yes
Impacted By Terrain Shadows
No
Status
Operational
Input By
Guy Schumann
Notes
FloodSENS outputs can be visualized in 3D upon request
User Feedback